Winter school of System Analysis and AI

Introduction

This report uses the tidyverse package along with the SAFI dataset, which has columns that include:

• village
  • Name of village
• interview_date
  • Date of interview
• no_members
  • How many family members lived in a house
• years_liv
  • How many years respondent has lived in village or neighbouring village
• respondent_wall_type
  • Type of wall of house
• rooms
  • Number of rooms in house

We can also add a caption.

Village	Member Association	Mean Number of Members
Chirodzo	no	8.062500
Chirodzo	yes	7.818182
God	no	7.133333
God	yes	8.000000
Ruaca	no	7.178571
Ruaca	yes	9.500000

Text text

## Rows: 131 Columns: 45
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr   (5): village, respondent_wall_type, memb_assoc, affect_conflicts, inst...
## dbl   (8): key_ID, no_membrs, years_liv, rooms, liv_count, no_meals, number_...
## lgl  (31): bicycle, television, solar_panel, table, cow_cart, radio, cow_plo...
## dttm  (1): interview_date
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

## # A tibble: 33 × 3
##    village  items        percent
##    <chr>    <chr>          <dbl>
##  1 Chirodzo bicycle         43.6
##  2 Chirodzo television      38.5
##  3 Chirodzo solar_panel     48.7
##  4 Chirodzo table           28.2
##  5 Chirodzo cow_cart        15.4
##  6 Chirodzo radio           61.5
##  7 Chirodzo cow_plough      51.3
##  8 Chirodzo solar_torch     43.6
##  9 Chirodzo mobile_phone    64.1
## 10 Chirodzo motorcyle       33.3
## # ℹ 23 more rows

data <- interviews |>
  select(village) |>
  group_by(village) |>
  summarise(count = n())
data

## # A tibble: 3 × 2
##   village  count
##   <chr>    <int>
## 1 Chirodzo    39
## 2 God         43
## 3 Ruaca       49

In village Chirodzo live 39 people.

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© Yurii Kleban